Ramirez-Atencia, Cristian; Rodriguez-Fernandez, Victor; Camacho, David
A revision on multi-criteria decision making methods for multi-UAV mission planning support Journal Article
In: Expert Systems with Applications, vol. 160, pp. 113708, 2020, ISSN: 0957-4174.
@article{RAMIREZATENCIA2020113708,
title = {A revision on multi-criteria decision making methods for multi-UAV mission planning support},
author = {Cristian Ramirez-Atencia and Victor Rodriguez-Fernandez and David Camacho},
url = {https://www.sciencedirect.com/science/article/pii/S0957417420305327},
doi = {https://doi.org/10.1016/j.eswa.2020.113708},
issn = {0957-4174},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {Expert Systems with Applications},
volume = {160},
pages = {113708},
abstract = {Over the last decade, Unmanned Aerial Vehicles (UAVs) have been extensively used in many commercial applications due to their manageability and risk avoidance. One of the main problems considered is the mission planning for multiple UAVs, where a solution plan must be found satisfying the different constraints of the problem. This problem has multiple variables that must be optimized simultaneously, such as the makespan, the cost of the mission or the risk. Therefore, the problem has a lot of possible optimal solutions, and the operator must select the final solution to be executed among them. In order to reduce the workload of the operator in this decision process, a Decision Support System (DSS) becomes necessary. In this work, a DSS consisting of ranking and filtering systems, which order and reduce the optimal solutions, has been designed. With regard to the ranking system, a wide range of Multi-Criteria Decision Making (MCDM) methods, including some fuzzy MCDM, are compared on a multi-UAV mission planning scenario, in order to study which method could fit better in a multi-UAV decision support system. Expert operators have evaluated the solutions returned, and the results show, on the one hand, that fuzzy methods generally achieve better average scores, and on the other, that all of the tested methods perform better when the preferences of the operators are biased towards a specific variable, and worse when their preferences are balanced. For the filtering system, a similarity function based on the proximity of the solutions has been designed, and on top of that, a threshold is tuned empirically to decide how to filter solutions without losing much of the hypervolume of the space of solutions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ramirez-Atencia, Cristian
Automated mission planning and decision support systems for multiple unmanned aerial vehicles PhD Thesis
Universidad Autónoma de Madrid, 2018.
@phdthesis{ramirez2018automated,
title = {Automated mission planning and decision support systems for multiple unmanned aerial vehicles},
author = {Cristian Ramirez-Atencia},
url = {http://hdl.handle.net/10486/686590},
year = {2018},
date = {2018-10-22},
school = {Universidad Autónoma de Madrid},
keywords = {},
pubstate = {published},
tppubtype = {phdthesis}
}
Ramirez-Atencia, Cristian; Rodriguez-Fernandez, Victor; Camacho, David
A multi-criteria decision support system for multi-UAV mission planning Incollection
In: Data Science and Knowledge Engineering for Sensing Decision Support, vol. 11, pp. 1083–1090, World Scientific, 2018, ISBN: 978-981-3273-22-1.
@incollection{ramirez2018multi,
title = {A multi-criteria decision support system for multi-UAV mission planning},
author = {Cristian Ramirez-Atencia and Victor Rodriguez-Fernandez and David Camacho},
doi = {10.1142/9789813273238_0137},
isbn = {978-981-3273-22-1},
year = {2018},
date = {2018-10-01},
booktitle = {Data Science and Knowledge Engineering for Sensing Decision Support},
volume = {11},
pages = {1083--1090},
publisher = {World Scientific},
series = {World Scientific Proceedings Series on Computer Engineering and Information Science},
abstract = {The Multi-UAV Mission Planning problem is focused on the search of a set of solutions that satisfy several constraints on the mission scenario and has some variables to be optimized, such as the makespan, the cost of the mission or the risk. Thus, there could exist a large number of solutions to the problem. It turns a big issue for the operator to select the final solution to execute among the many obtained. In order to reduce the operator workload, this work proposes a Multi-Criteria Decision Support System, which consists of a ranking function that sorts the solutions obtained. Several ranking functions have been tested in real mission scenarios with different operator profiles. Expert operators have evaluated the solutions returned in order to compare the different ranking systems and demonstrate the usefulness of the proposed approach.},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}